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hub / github.com/espnet/espnet / __init__

Method __init__

espnet2/train/preprocessor.py:1745–1828  ·  view source on GitHub ↗
(
        self,
        train: bool,
        train_spk2enroll: Optional[str] = None,
        enroll_segment: int = None,
        load_spk_embedding: bool = False,
        load_all_speakers: bool = False,
        # inherited from EnhPreprocessor
        rir_scp: Optional[str] = None,
        rir_apply_prob: float = 1.0,
        noise_scp: Optional[str] = None,
        noise_apply_prob: float = 1.0,
        noise_db_range: str = "3_10",
        short_noise_thres: float = 0.5,
        speech_volume_normalize: float = None,
        speech_name: str = "speech_mix",
        speech_ref_name_prefix: str = "speech_ref",
        noise_ref_name_prefix: str = "noise_ref",
        dereverb_ref_name_prefix: str = "dereverb_ref",
        use_reverberant_ref: bool = False,
        num_spk: int = 1,
        num_noise_type: int = 1,
        sample_rate: int = 8000,
        force_single_channel: bool = False,
        channel_reordering: bool = False,
        categories: Optional[List] = None,
        data_aug_effects: List = None,
        data_aug_num: List[int] = [1, 1],
        data_aug_prob: float = 0.0,
        speech_segment: Optional[int] = None,
        avoid_allzero_segment: bool = True,
        flexible_numspk: bool = False,
    )

Source from the content-addressed store, hash-verified

1743 """Preprocessor for Target Speaker Extraction."""
1744
1745 def __init__(
1746 self,
1747 train: bool,
1748 train_spk2enroll: Optional[str] = None,
1749 enroll_segment: int = None,
1750 load_spk_embedding: bool = False,
1751 load_all_speakers: bool = False,
1752 # inherited from EnhPreprocessor
1753 rir_scp: Optional[str] = None,
1754 rir_apply_prob: float = 1.0,
1755 noise_scp: Optional[str] = None,
1756 noise_apply_prob: float = 1.0,
1757 noise_db_range: str = "3_10",
1758 short_noise_thres: float = 0.5,
1759 speech_volume_normalize: float = None,
1760 speech_name: str = "speech_mix",
1761 speech_ref_name_prefix: str = "speech_ref",
1762 noise_ref_name_prefix: str = "noise_ref",
1763 dereverb_ref_name_prefix: str = "dereverb_ref",
1764 use_reverberant_ref: bool = False,
1765 num_spk: int = 1,
1766 num_noise_type: int = 1,
1767 sample_rate: int = 8000,
1768 force_single_channel: bool = False,
1769 channel_reordering: bool = False,
1770 categories: Optional[List] = None,
1771 data_aug_effects: List = None,
1772 data_aug_num: List[int] = [1, 1],
1773 data_aug_prob: float = 0.0,
1774 speech_segment: Optional[int] = None,
1775 avoid_allzero_segment: bool = True,
1776 flexible_numspk: bool = False,
1777 ):
1778 super().__init__(
1779 train,
1780 rir_scp=rir_scp,
1781 rir_apply_prob=rir_apply_prob,
1782 noise_scp=noise_scp,
1783 noise_apply_prob=noise_apply_prob,
1784 noise_db_range=noise_db_range,
1785 short_noise_thres=short_noise_thres,
1786 speech_volume_normalize=speech_volume_normalize,
1787 speech_name=speech_name,
1788 speech_ref_name_prefix=speech_ref_name_prefix,
1789 noise_ref_name_prefix=noise_ref_name_prefix,
1790 dereverb_ref_name_prefix=dereverb_ref_name_prefix,
1791 use_reverberant_ref=use_reverberant_ref,
1792 num_spk=num_spk,
1793 num_noise_type=num_noise_type,
1794 sample_rate=sample_rate,
1795 force_single_channel=force_single_channel,
1796 channel_reordering=channel_reordering,
1797 categories=categories,
1798 data_aug_effects=data_aug_effects,
1799 data_aug_num=data_aug_num,
1800 data_aug_prob=data_aug_prob,
1801 speech_segment=speech_segment,
1802 avoid_allzero_segment=avoid_allzero_segment,

Callers

nothing calls this directly

Calls 1

__init__Method · 0.45

Tested by

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